Existing methods of representing vehicles in a virtual environment typically involve computer simulations. In a common computer simulation, computers are used to simulate vehicle dynamics using algorithms. The accuracy of computer simulations heavily relies on how well the models are validated. Validation is often time-consuming and expensive, but necessary to generate high fidelity computer simulations. Even when the computer simulation is thoroughly validated, the computer simulation is still limited as a mathematical representation of reality and is thus inherently an approximation at best of the kinematics of vehicles operation. Such approximations have a tendency to undesirably simplify many of the complexities of the actual system that is being represented.
Another approach is to use historical data collected from a real environment to assist in the creation of a virtual environment. However, historical data may be difficult to obtain, require interaction with environments which may not be available, and may not include enough flexibility to make ad hoc simulations.
Generally speaking, traditional methods of representing vehicles in a virtual environment may benefit from improved dynamic accuracy and increased feasibility. Accordingly, there is a need for improved techniques that create a more accurate and feasible method of representing vehicles in a virtual environment.